Optimization Group Meetings

You can subscribe to an iCalendar of these meetings at http://iridia.ulb.ac.be/Calendars/publish.php/_NUC_Optimization.ics

Breakfast Meetings

Purpose

Breakfast meetings are informal meetings where there is a general discussion or someone presents their work. And additional goal is to have breakfast together.

Organization

1. Send an email to the responsible of Optimization Meetings. Mention your name, your affiliation, the date, time and room, and a short summary of what you are going to talk about.
2. Add a new entry to the table below.
3. Bring breakfast.

History of Breakfast Meetings

Date	Presenter	Summary
2013-09-12	Leslie Perez	Tuning and irace
2011-03-10	Stefanie Kritzinger	A Unified Framework for Routing Problems with Fixed Fleet Size
2010-12-21	Paola Pellegrini	Off-line vs. On-line Tuning: A Study on MAX-MIN Ant System for the TSP
2010-10-19	Stefano Benedettini	Experiments on Boolean Network Design by Local Search Algorithms.
2010-05-20	Marco Montes de Oca	The social learning strategies tournament, organized as part of the cultaptation project, and its results were described. No ideas about algorithm portfolios were discussed.
2010-05-??	Renaud Lenne	???
2010-04-29	Franco Mascia	The maximum clique problem, state of the art and ACO [1] [2] [3]
2010-03-18	Sabrina Oliveira	Achieved results from the application of the Population Based Ant Colony Optimisation algorithm to TSP.
2010-02-11	Sara Ceschia	An overview of Container Loading Problems.
2010-01-21	Yuan, Zhi (Eric)	Rice cooker vs. the idea of tuning.
2010-01-07	Thomas Stüztle	General discussion about the optimization group.

Literature Sessions

Purpose

The goal of the Literature Sessions is to examine and discuss particularly interesting papers from the research literature. For each session, one paper will be selected, there will be a short presentation (10-15 minutes) about the contents, and a discussion will ensue. Sessions will last around 40-45 minutes. Attendants should read the paper before the session in order to have a productive discussion.

Organization

1. Send an email to the responsible of Optimization Meetings. Mention your name, your affiliation, the date, time and room, a reference to the paper and the URL where it can be obtained. Also, attach the paper in PDF.
2. Add a new entry to the table below. Use YYY-MM-DD (year-month-day) format for the date. Please add a complete bibliographic reference (you may find it in the homepages of the authors) and a hyperlink to a PDF (links to http://dx.doi.org are preferred).

History of Literature Sessions

Date	Presenter	Paper discussed
2014-02-20	Thomas Stutzle	A unified solution framework for multi-attribute vehicle routing problems. Thibaut Vidal, Teodor Gabriel Crainic, Michel Gendreau, and Christian Prins. http://dx.doi.org/10.1016/j.ejor.2013.09.045
2013-10-03	Leonardo Bezerra	Robust Benchmark Set Selection for Boolean Constraint Solvers. Holger Hoos, Benjamin Kaufmann, Torsten Schaub and Marius Schneider - Proceedings of the 7th International Conference on Learning and Intelligent Optimization (LION 7), to appear, 2013. http://www.cs.ubc.ca/~hoos/Publ/HooEtAl13-preprint.pdf Quantifying Homogeneity of Instance Sets for Algorithm Configuration. Marius Schneider and Holger H. Hoos - Proceedings of the 6th International Conference on Learning and Intelligent Optimization (LION 6), pp. 190-204, 2012. http://www.cs.ubc.ca/~hoos/Publ/SchHoo12.pdf
2013-09-12	Manuel López-Ibáñez	Automated Parameter Tuning Framework for Heterogeneous and Large Instances: Case study in Quadratic Assignment Problem Lindawati, Zhi Yuan, Hoong Chuin Lau & Feida Zhu. http://lion.disi.unitn.it/intelligent-optimization//LION7/Lindawati-Yuan-Lau-Zhu_Automated%20Parameter%20Tuning.pdf
2013-04-11	Leslie Perez	C. Ansótegui, M. Sellmann, and K. Tierney, “A Gender-Based Genetic Algorithm for the Automatic Configuration of Algorithms,” in Principles and Practice of Constraint Programming - CP 2009, I. P. Gent, Ed. Springer Berlin Heidelberg, 2009, pp. 142–157. http://itu.dk/people/kevt/papers/gga-cp2009.pdf
2012-10-18	Manuel López-Ibáñez	Yuri Malitsky, Meinolf Sellmann: Instance-Specific Algorithm Configuration as a Method for Non-Model-Based Portfolio Generation. CPAIOR 2012: 244-259 http://dx.doi.org/10.1007/978-3-642-29828-8_16
2012-10-12	Tianjun Liao	Bernd Bischl, Olaf Mersmann, Heike Trautmann, and Mike Preuß. 2012. Algorithm selection based on exploratory landscape analysis and cost-sensitive learning. In Proceedings of the fourteenth international conference on Genetic and evolutionary computation conference (GECCO 2012), Terence Soule (Ed.). ACM, New York, NY, USA, 313-320. DOI:10.1145/2330163.2330209 Olaf Mersmann, Bernd Bischl, Heike Trautmann, Mike Preuss, Claus Weihs, and Günter Rudolph. 2011. Exploratory landscape analysis. In Proceedings of the 13th annual conference on Genetic and evolutionary computation (GECCO 2011), Natalio Krasnogor (Ed.). ACM, New York, NY, USA, 829-836. DOI:10.1145/2001576.2001690
2012-04-19	Franco Mascia	E.K. Burke, M.R. Hyde, and G. Kendall. Grammatical Evolution of Local Search Heuristics. IEEE Transactions on Evolutionary Computation, 99, 2011. doi: 10.1109/TEVC.2011.2160401 PDF
2012-04-03	Jérémie Dubois-Lacoste	On the automatic discovery of variants of the NEH procedure for flow shop scheduling using genetic programming. J A Vázquez-Rodríguez and G Ochoa.Journal of the Operational Research Society (2011) 62, 381–396. doi:10.1057/jors.2010.132
2011-12-08	Zhi Yuan	Frank Hutter, Holger Hoos, and Kevin Leyton-Brown. Sequential Model-Based Optimization for General Algorithm Configuration. In Proceedings of Learning and Intelligent Optimization (LION 5), 2011. PDF: [4]
2011-11-24	Manuel López-Ibáñez	Ender Özcan and Andrew J. Parkes. 2011. Policy matrix evolution for generation of heuristics. In Proceedings of the 13th annual conference on Genetic and evolutionary computation (GECCO 2011), Natalio Krasnogor (Ed.). ACM, New York, NY, USA, 2011-2018. DOI: 10.1145/2001576.2001846
2011-02-04	Paola Pellegrini	HAL: A Framework for the Automated Analysis and Design of High-Performance Algorithms. By Christopher Nell, Chris Fawcett, Holger H. Hoos, and Kevin Leyton-Brown. PDF
2010-12-17	Marco Montes de Oca	A. LaTorre, S. Muelas, and J.-M. Peña. A MOS-based dynamic memetic differential evolution algorithm for continuous optimization: a scalability test. Soft Computing. Special issue on Scalability of Evolutionary Algorithms and other Metaheuristics for Large Scale Continuous Optimization Problems. DOI 10.1007/s00500-010-0646-3
2010-11-10	Manuel López-Ibáñez	A Rigorous Analysis of the Harmony Search Algorithm--How the Research Community can be misled by a "novel" Methodology. Dennis Weyland. International Journal of Applied Metaheuristic Computing, volume 1-2, April-June 2010, pages 50-60. DOI: 10.4018/jamc.2010040104 Survival of the Fittest Algorithm or the Novelest Algorithm?: The Existence Reason of the Harmony Search Algorithm. Zong Woo Geem.
2010-09-23	Gianpiero Francesca	Wenyin Gong, Álvaro Fialho and Zhihua Cai. Adaptive Strategy Selection in Differential Evolution. In J. Branke et al., eds.: "GECCO'10: Proc. 12th Annual Conference on Genetic and Evolutionary Computation", ACM Press : p. 409-416. July 2010. [5] Álvaro Fialho, Marc Schoenauer and Michele Sebag. Toward Comparison-based Adaptive Operator Selection. In J. Branke et al., eds.: "GECCO'10: Proc. 12th Annual Conference on Genetic and Evolutionary Computation", ACM Press : p. 767-774. July 2010. [6]
2010-06-03	Tianjun Liao	Population-Based Algorithm Portfolios for Numerical Optimization. Peng, F. Tang, K.Chen, G.Yao, X. IEEE Transactions on Evolutionary Computation. DOI: 10.1109/TEVC.2010.2040183
2010-05-07	Zhi (Eric) Yuan	Hydra: Automatically Configuring Algorithms for Portfolio-Based Selection. L. Xu, H.H. Hoos, K. Leyton-Brown. To appear at the Conference of the Association for the Advancement of Artificial Intelligence (AAAI-10), 2010. [7]
2010-03-04	Sara Ceschia	A. Schaerf and L. Di Gaspero. Slides of the tutorial "An Overview of Local Search Software Tools" given at "Learning and Intelligent OptimizatioN (LION 2007)", December 8-12, 2007, Trento, Italy. L. Di Gaspero and A. Schaerf. EASY LOCAL++: An object-oriented framework for flexible design of local search algorithms. Software — Practice & Experience, 33(8):733–765, July 2003. [8] S. Cahon, N. Melab and T. El Ghazali. ParadisEO: A Framework for the Reusable Design of Parallel and Distributed Metaheuristics. Journal of Heuristics, 10(3):357-380, November 2004. [9]
2010-02-19	Sabrina M. de Oliveira	A study on the use of non-parametric tests for analyzing the evolutionary algorithms' behaviour: a case study on the CEC'2005 Session on Real Parameter Optimization. S. Garcia, D. Molina, M. Lozano, F. Herrera - Journal of Heuristics, Volume 15, pp. 617-644, 2009. [10]
2010-02-04	Thomas Stüztle	Analyzing Bandit-based Adaptive Operator Selection Mechanisms. Álvaro Fialho, Luis Da Costa, Marc Schoenauer and Michéle Sebag.
2010-01-14	Jérémie Dubois-Lacoste	SATzilla: Portfolio-based Algorithm Selection for SAT. L. Xu, F. Hutter, H. H. Hoos, K. Leyton-Brown - Journal of Artificial Intelligence Research, Volume 32, pp. 565-606, 2008. [11]
2009-12-11	Manuel López-Ibáñez	SATenstein: Automatically Building Local Search SAT Solvers From Components. Ashiqur R. KhudaBukhsh, Lin Xu, Holger H. Hoos and Kevin Leyton-Brown - Proceedings of the 21st International Joint Conference on Artificial Intelligence (IJCAI-09), pp. 517-524, 2009. [12]

Other Previous Meetings

See Minutes and agendas from previous meetings.